Community detection in airline networks : an empirical analysis of American vs. Southwest airlines

In this paper, we develop a route-traffic-based method for detecting community structures in airline networks. Our model is both an application and an extension of the Clauset-Newman-Moore (CNM) modularity maximization algorithm, in that we apply the CNM algorithm to large airline networks, and take both route distance and passenger volumes into account. Therefore, the relationships between airports are defined not only based on the topological structure of the network but also by a traffic-driven indicator. To illustrate our model, two case studies are presented: American Airlines and Southwest Airlines. Results show that the model is effective in exploring the characteristics of the network connections, including the detection of the most influential nodes and communities on the formation of different network structures. This information is important from an airline operation pattern perspective to identify the vulnerability of networks

Leveraging AI for small and medium-sized enterprises (SMEs) : exploring real-world applications of AI in business

The purpose of this bachelor thesis is to find out where artificial intelligence (AI) specifically could be applicable in small and medium-sized enterprises (SMEs) when it comes to business fields such as retail, marketing, customer service, or similar crucial business operations. The current study's primary focus is to find out the possible AI applications in SMEs, the advantages, and most importantly challenges of AI adoption in SMEs by a mixed methods research approach adhering to literature review and case study. The findings of this study show the most used AI applications in SMEs include automated customer service, process automation, supply chain optimization, data analysis, and marketing optimization and automation. Besides, the research highlights one emerging application - AI-powered digital human that has the potential to revolutionize many industries. The benefits of each AI application in SMEs mentioned above were examined. The challenges such as high implementation costs and lack of technical expertise were also identified and discussed. The study concludes with recommendations for SMEs on how to successfully leverage AI technologies